WO2020066348A1 - Procédé de détermination - Google Patents

Procédé de détermination Download PDF

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Publication number
WO2020066348A1
WO2020066348A1 PCT/JP2019/031862 JP2019031862W WO2020066348A1 WO 2020066348 A1 WO2020066348 A1 WO 2020066348A1 JP 2019031862 W JP2019031862 W JP 2019031862W WO 2020066348 A1 WO2020066348 A1 WO 2020066348A1
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Prior art keywords
phase difference
sphere
index value
aggregate
difference image
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PCT/JP2019/031862
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English (en)
Japanese (ja)
Inventor
崇市郎 中村
祥 小野澤
龍介 大▲崎▼
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富士フイルム株式会社
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Priority to EP19865460.0A priority Critical patent/EP3859006A4/fr
Priority to JP2020548139A priority patent/JP7123155B2/ja
Publication of WO2020066348A1 publication Critical patent/WO2020066348A1/fr
Priority to US17/182,569 priority patent/US11869181B2/en

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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/41—Refractivity; Phase-affecting properties, e.g. optical path length
    • G01N21/45—Refractivity; Phase-affecting properties, e.g. optical path length using interferometric methods; using Schlieren methods
    • G01N21/453—Holographic interferometry
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/02—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving viable microorganisms
    • G—PHYSICS
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    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/502—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing non-proliferative effects
    • G01N33/5032—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing non-proliferative effects on intercellular interactions
    • G—PHYSICS
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5044—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics involving specific cell types
    • G01N33/5073—Stem cells
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
    • C12M1/00—Apparatus for enzymology or microbiology
    • C12M1/34—Measuring or testing with condition measuring or sensing means, e.g. colony counters
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03H—HOLOGRAPHIC PROCESSES OR APPARATUS
    • G03H1/00—Holographic processes or apparatus using light, infrared or ultraviolet waves for obtaining holograms or for obtaining an image from them; Details peculiar thereto
    • G03H1/04—Processes or apparatus for producing holograms
    • G03H1/08—Synthesising holograms, i.e. holograms synthesized from objects or objects from holograms
    • G03H1/0866—Digital holographic imaging, i.e. synthesizing holobjects from holograms
    • G—PHYSICS
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    • G03H—HOLOGRAPHIC PROCESSES OR APPARATUS
    • G03H1/00—Holographic processes or apparatus using light, infrared or ultraviolet waves for obtaining holograms or for obtaining an image from them; Details peculiar thereto
    • G03H1/04—Processes or apparatus for producing holograms
    • G03H1/08—Synthesising holograms, i.e. holograms synthesized from objects or objects from holograms
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    • G06T2207/30004—Biomedical image processing
    • G06T2207/30024—Cell structures in vitro; Tissue sections in vitro

Definitions

  • the disclosed technology relates to a determination method for determining a state of an aggregate of a plurality of cells.
  • Patent Literature 1 discloses a method for determining the degree of differentiation of pluripotent stem cells using the flatness of the surface of one cell or the flatness of the surface of a cell population as an index of the degree of differentiation.
  • Patent Literature 2 discloses a multi-layer colony containing a multipotent stem cell in which a differentiated colony containing a differentiated pluripotent stem cell, an undifferentiated colony containing only an undifferentiated pluripotent stem cell, and a multi-layered pluripotent stem cell are stacked based on the luminance in a captured image. Is described. In this method, a colony having a region with a luminance higher than the first luminance threshold is determined to be a differentiated colony. In addition, a colony having only a region with a luminance equal to or lower than the first threshold is determined to be an undifferentiated colony.
  • a colony having only a region having a luminance equal to or lower than the first threshold and having a luminance equal to or higher than the second threshold is determined to be an undifferentiated colony.
  • a colony having an area with a luminance lower than the second threshold is determined to be a multilayer colony.
  • Patent Document 3 discloses an image input step of inputting a captured image obtained by capturing cells in a neural differentiation process, a neurite extraction step of extracting neurites appearing in cells in a neural differentiation process from an original image based on the captured image, A neurite correspondence determination step of determining a state of the extracted neurite is described.
  • Patent Document 4 discloses a method for presenting a cell state, wherein a time-lapse profile of the cell is obtained by monitoring a time-lapse of a gene state associated with at least one gene selected from genes derived from the cell. A method is described that includes the steps of presenting the temporal profile.
  • a culture method capable of mass-producing cells there is known a three-dimensional culture method in which spheres, which are aggregates of cells, are cultured in a state of being suspended in a medium.
  • a technique for non-destructively and simply evaluating the quality of cells in a sphere state is required from the viewpoint of easy process control.
  • no method has been established for evaluating spheres of various sizes randomly present in the three-dimensional space, and it is difficult to directly observe the cell density and survival status, especially inside the sphere. is there. For this reason, as described in Patent Literatures 1-3, evaluation using a conventional two-dimensional culture technique has been performed.
  • the disclosed technique aims to non-destructively and easily determine the state of aggregates of a plurality of cells formed by three-dimensional culture.
  • the determination method generates a phase difference image of an aggregate from a hologram obtained by imaging an aggregate of a plurality of cells, and indicates the randomness of the array of the amount of phase difference in a plurality of pixels forming the phase difference image. Deriving a first index value and determining a state of a cell constituting the aggregate based on the first index value. According to the determination method according to the disclosed technology, the state of the aggregate of a plurality of cells formed by three-dimensional culture can be determined nondestructively and easily.
  • the first index value may be a value determined according to a degree of deviation from a circle of a shape of a region surrounded by equiphase lines connecting pixels having the same phase difference amount in the phase difference image.
  • the minimum value of the phase difference amount in a predetermined range in a plurality of pixels constituting the phase difference image is ⁇ 0
  • the maximum value is ⁇ N
  • the circumference of the isophase line at an arbitrary phase ⁇ in the predetermined range is set.
  • the average phase fluctuation ⁇ defined by the following equation (3) is It can be used as an index value of 1.
  • the first index value may be derived based on a shape component removal image that has been subjected to a process of removing a component depending on the shape of the aggregate from the phase difference image.
  • a shape component removal image that has been subjected to a process of removing a component depending on the shape of the aggregate from the phase difference image.
  • an autocorrelation function or a two-dimensional power spectrum derived based on the shape component removed image may be derived as the first index value.
  • the determination method according to the disclosed technology may include performing a determination regarding the survival rate of the cells constituting the aggregate based on the first index value. Further, when the cells constituting the aggregate are stem cells, the determination method according to the disclosed technology may include performing a determination regarding the undifferentiation rate of the stem cells constituting the aggregate based on the first index value. . By making a determination on the cell survival rate or undifferentiation rate based on the first index value, the determination can be made nondestructively and easily.
  • the determination method derives a second index value indicating a correlation between the first index value and the particle size of the aggregate for a plurality of aggregates included in the determination target lot, The determination may be performed on the determination target lot based on the index value. This makes it possible to perform a non-destructive and simple determination on the determination target lot.
  • the determination method according to the disclosed technology may include performing a determination regarding the survival rate of the cells included in the determination target lot based on the second index value. Further, when the cells constituting the aggregate are stem cells, the determination method according to the disclosed technique includes performing a determination regarding the undifferentiation rate of the stem cells included in the determination target lot based on the second index value. obtain. By performing the determination regarding the survival rate or the undifferentiation rate of the cells included in the determination target lot based on the second index value, the determination can be performed nondestructively and easily.
  • FIG. 1 is a diagram illustrating an example of a configuration of an imaging system used for performing a determination method according to an embodiment of the disclosed technology.
  • FIG. 4 is a diagram illustrating an example of a hologram used for performing a determination method according to an embodiment of the disclosed technology. It is a figure showing an example of a Fourier transform picture of a sphere. It is a figure showing an example of a phase contrast picture before unwrapping of a sphere. It is a figure showing an example of a phase contrast picture after unwrapping of a sphere.
  • FIG. 4 is a diagram illustrating a concept of a phase difference image according to an embodiment of the disclosed technology.
  • FIG. 4 is an explanatory diagram related to focusing of a phase difference image according to an embodiment of the disclosed technology.
  • 11 is an example of a hardware configuration of a computer that performs an autofocus process according to an embodiment of the disclosed technology.
  • 11 is a flowchart illustrating an example of a flow of an autofocus process according to an embodiment of the disclosed technology.
  • 9 is a graph illustrating an example of a relationship between a focus position and a variation in a phase difference amount in a phase difference image of a sphere according to the embodiment of the disclosed technology. It is a figure showing a phase difference picture of a sphere.
  • FIG. 8B is a contour diagram illustrating a distribution of a phase difference amount in the phase difference image illustrated in FIG. 8A. It is a figure showing a phase difference picture of a sphere.
  • FIG. 9B is a contour diagram illustrating a distribution of a phase difference amount in the phase difference image illustrated in FIG. 9A. It is a figure showing a phase difference picture of a sphere.
  • FIG. 10B is a contour diagram illustrating a distribution of a phase difference amount in the phase difference image illustrated in FIG. 10A. It is a figure showing a phase difference picture of a sphere.
  • FIG. 11B is a contour diagram illustrating a distribution of a phase difference amount in the phase difference image illustrated in FIG. 11A.
  • 5 is a graph showing an example of a correlation between a sphere particle size and an average phase fluctuation. It is a graph which shows an example of the correlation between the constant A and the undifferentiation rate.
  • FIG. 5 is a graph showing an example of a correlation between a sphere particle size and an average phase fluctuation. It is a graph which shows the correlation between the constant A and the cell survival rate. It is a figure which shows an example of the image (right figure) which extracted the randomness (spatial variation) of the phase difference amount from the phase difference image of the sphere.
  • FIG. 4 is a diagram illustrating a two-dimensional power spectrum derived for an image that has been subjected to a process of removing a component depending on the shape of a sphere from a phase difference image of the sphere.
  • the determination method generates a phase difference image of an aggregate (sphere) from a hologram obtained by imaging an aggregate (sphere) of a plurality of cells, and calculates a position in a plurality of pixels constituting the phase difference image. This is a value that derives a first index value indicating the randomness of the sequence of the amount of phase difference, and determines the state of the cells constituting the aggregate (sphere) based on the first index value. According to this determination method, the state of the aggregate (sphere) can be determined nondestructively and easily.
  • FIG. 1 is a diagram illustrating an example of a configuration of an imaging system 1 used for performing a determination method according to an embodiment of the disclosed technology.
  • the imaging system 1 includes a hologram optical system 10 for acquiring a sphere hologram using a known digital holography technique.
  • Digital holography technology uses an image sensor to capture an image generated by interference between object light transmitted or reflected by an object and reference light that is coherent to the object light, and the image obtained by the imaging is based on light propagation. This is a technique for restoring the wavefront of light waves from an object by performing numerical calculations. According to the digital holography technique, the phase distribution of an object can be quantified, and three-dimensional information of the object can be obtained without mechanically moving a focal position.
  • the hologram optical system 10 includes a laser light source 11, beam splitters 12, 18, collimating lenses 13, 21, an objective lens 15, a dichroic mirror 34, an imaging lens 17, and a CMOS (Complementary Metal Oxide Semiconductor) camera 19. I have.
  • the sphere as the sample 14 set on the sample stage is arranged between the collimator lens 13 and the objective lens 15.
  • the laser light source 11 for example, a HeNe laser having a wavelength of 632.8 nm can be used.
  • the laser light emitted from the laser light source 11 is split into two laser lights by the beam splitter 12.
  • One of the two laser beams is used as an object beam, and the other is used as a reference beam.
  • the object light is collimated by a collimating lens 13 and then applied to a sphere which is a sample 14 set on a sample stage.
  • the image of the object light transmitted through the sphere is enlarged by the objective lens 15.
  • the object light that has passed through the objective lens 15 passes through the dichroic mirror 34, is converted into parallel light again by the imaging lens 17, and is then imaged on the imaging surface of the CMOS camera 19 via the beam splitter 18.
  • the reference light is guided by the optical fiber 20 to a position before the collimator lens 21.
  • the reference light emitted from the optical fiber 20 is converted into parallel light by the collimator lens 21, and enters the imaging surface of the CMOS camera 19 via the beam splitter 18.
  • a hologram generated by interference between the object light and the reference light is recorded by the CMOS camera 19. Note that an off-axial optical system in which the optical axes of the object light and the reference light incident on the imaging surface of the CMOS camera 19 are different from each other may be configured.
  • a phase difference image of a sphere can be obtained without destroying the sphere and without damaging cells constituting the sphere.
  • the configuration of the imaging system 1 described above is merely an example, and is not limited to the above configuration.
  • any imaging system that can acquire a hologram using a digital hologram technology can be used.
  • FIG. 2A the hologram illustrated in FIG. 2A acquired by the CMOS camera 19 is subjected to two-dimensional Fourier transform to extract a complex amplitude component of only the object light.
  • FIG. 2B is an example of a Fourier transform image of the sphere obtained by this processing.
  • FIG. 2C is an example of a phase difference image before unwrapping of the sphere obtained by this processing.
  • the sphere phase at this point has been convolved to a value between 0 and 2 ⁇ . Therefore, for example, by applying a phase connection (unwrapping) method such as Unweighted Least Squares (unweighted least squares method) or Flynn's Algorithm (Flinn's algorithm), a portion of 2 ⁇ or more is joined, and FIG.
  • a phase difference image of the final sphere as illustrated can be obtained.
  • Many unwrapping methods have been proposed, and an appropriate method that does not cause phase mismatch may be appropriately selected.
  • Figure 3 is a diagram showing the concept of a phase difference image I P.
  • the lower part of FIG. 3 is an image obtained by three-dimensionally displaying the amount of phase difference at each pixel k of the phase difference image I P.
  • the upper part of FIG. 3 is a diagram showing an amount of phase difference at each pixel k of the phase difference image I P in grayscale on a plane.
  • phase difference image I P the amount of phase difference theta in the phase difference image I P, the phase of the background (non-existing regions of the spheres) existing in the same focal plane of the phase contrast image I P and theta B, a region in the presence of Spheres
  • phase is represented by the following equation (1).
  • phase in this specification is a phase of an electric field amplitude when light is regarded as an electromagnetic wave, and is used in a more general sense.
  • phase difference amount theta k in each pixel k of the phase difference image I P can be represented by the following equation (2).
  • n k is the index of refraction of the spheres in the region corresponding to each image k of the phase difference image I P
  • d k is the thickness of the spheres at the site corresponding to each pixel k of the phase difference image I P
  • ⁇ is the wavelength of the object light in the hologram optical system 10.
  • the phase difference image of the sphere is an image showing the optical path length distribution of the object light transmitted through the sphere. Since the optical path length in the sphere corresponds to the product of the refractive index of the sphere and the thickness of the sphere, the phase difference image of the sphere has the refractive index and the thickness of the sphere as shown in equation (2). It contains information on the size (shape).
  • phase difference image From the phase difference image out of focus on the sphere, accurate information matching the actual state of the sphere cannot be obtained due to the influence of the spread due to diffraction. Therefore, when acquiring a phase difference image from the hologram acquired by the CMOS camera 19, it is preferable to focus on the sphere.
  • focus on the sphere means to obtain a phase difference image sliced near the center of the spherical sphere.
  • the focusing of the phase difference image be automated without manual operation.
  • automating focusing it is possible to eliminate arbitrariness by an operator and further reduce processing time.
  • the present inventors have found an automatable focusing technique described below.
  • the left graph in FIG. 4 is a graph showing an example of the relationship between the position of the sphere in the plane direction and the amount of phase difference in the phase difference image, and the solid line corresponds to the state where the sphere is in focus, and the dotted line is the sphere. Corresponds to the state of being out of focus. When the sphere is in focus, a steep peak appears at a specific position in the phase difference image. On the other hand, when the sphere is out of focus, the peak is lower and gentler than when the sphere is in focus.
  • the right graph of FIG. 4 is an example of the histogram of the phase difference amount in the phase difference image of the sphere, and the solid line corresponds to the state where the sphere is in focus, and the dotted line corresponds to the state where the sphere is not in focus. I do.
  • the half width w of the curve (variation in phase difference amount) becomes relatively large
  • the half width w of the curve (variation in phase difference amount) Is relatively small.
  • a phase difference image of a sphere is acquired for each different focus position (slice position), and a half width w (variation of the phase difference amount) of the curve in the histogram of the phase difference amount is obtained for each of the acquired phase difference images.
  • the focusing can be realized by extracting the phase difference image having the maximum half value width w among the obtained half value widths w as the phase difference image focused on the sphere.
  • FIG. 5 is an example of a hardware configuration of a computer 500 that performs an autofocus process for automatically performing the above-described focusing.
  • the computer 500 includes a CPU (Central Processing Unit) 501, a main storage device 502 as a temporary storage area, a nonvolatile auxiliary storage device 503, and a communication I / F (InterFace) 504 for performing communication with the CMOS camera 19. , And a display unit 505 such as a liquid crystal display.
  • the CPU 501, the main storage device 502, the auxiliary storage device 503, the communication I / F 504, and the display unit 505 are connected to a bus 507, respectively.
  • the auxiliary storage device 503 stores an autofocus program 506 describing the procedure of the above autofocus processing.
  • the computer 500 performs an autofocus process when the CPU 501 executes the autofocus program 506.
  • FIG. 6 is a flowchart illustrating an example of the flow of the autofocus process performed by the computer 500.
  • step S1 the CPU 501 obtains a sphere hologram from the CMOS camera 19.
  • step S2 the CPU 501 generates a plurality of phase difference images having different focal positions (slice positions) from the obtained hologram.
  • step S3 the CPU 501 derives a variation in the amount of phase difference for each of the phase difference images for each focal position (slice position). For example, the CPU 501 may derive the difference between the maximum value and the minimum value of the phase difference amount in the phase difference image as the variation of the phase difference amount in the phase difference image.
  • step S4 the CPU 501 converts the phase difference image in which the variation of the phase difference amount derived in step S3 is maximum among the phase difference images having different focal positions (slice positions) from each other into the focused phase difference image. Extract as an image.
  • FIG. 7 is a graph showing an example of the relationship between the focus position (slice position) and the variation in the amount of phase difference in the phase difference image of the sphere.
  • FIG. 7 exemplifies, with a graph, phase difference images of spheres corresponding to focal positions of ⁇ 400 ⁇ m, ⁇ 200 ⁇ m, 0 ⁇ m, +200 ⁇ m, and +400 ⁇ m.
  • the focal position at which the variation in the amount of phase difference is maximum is 0 ⁇ m.
  • a phase difference image corresponding to a focus position of 0 ⁇ m at which the variation of the phase difference amount becomes maximum is extracted as a focused phase difference image.
  • the outline of the sphere is the sharpest.
  • the first index value indicating the randomness of the arrangement of the phase difference amounts in the plurality of pixels forming the phase difference image of the sphere is derived.
  • the method includes determining a state of a cell constituting the sphere based on the first index value.
  • FIG. 8A shows a phase difference of a sphere which is an aggregate of iPS cells extracted from a culture lot in which the ratio of iPS cells maintaining an undifferentiated state in the lot (hereinafter referred to as undifferentiation rate) is 99%. It is a figure showing the example of a typical image.
  • FIG. 8B is a contour diagram showing a distribution of a phase difference amount in the phase difference image shown in FIG. 8A.
  • FIG. 9A is a diagram illustrating a representative example of a phase contrast image of a sphere that is an aggregate of iPS cells extracted from a culture lot with an undifferentiation rate of 87%.
  • FIG. 9B is a contour diagram showing a distribution of a phase difference amount in the phase difference image shown in FIG. 9A.
  • Spheres in lots with a higher undifferentiation rate have higher internal homogeneity compared to spheres in lots with a lower undifferentiation rate (ie, germ layer differentiation is progressing) it is conceivable that. Therefore, in the phase difference image of the sphere in the lot having a relatively high undifferentiation rate, as shown in FIG. 8B, the shape of the region surrounded by the equiphase lines connecting the pixels having the same phase difference amount is circular. The shapes are close, and the equiphase lines are distributed concentrically. On the other hand, in the phase difference image of the sphere in the lot having a relatively low undifferentiation rate, as shown in FIG.
  • the arrangement of the phase difference amounts in a plurality of pixels constituting the phase difference image becomes random, The shape of the area surrounded by is broken. That is, the progress of differentiation of the cells constituting the sphere is reflected in the randomness of the arrangement of the phase difference amounts in the plurality of pixels constituting the phase difference image of the sphere. Therefore, it is possible to quantify the progress of differentiation of the cells constituting the sphere by using the index value indicating the randomness of the arrangement of the phase difference amounts in the plurality of pixels constituting the phase difference image of the sphere.
  • the index value is surrounded by equal phase lines connecting the pixels having the same phase difference amount in the phase difference image of the sphere.
  • An index value determined according to the degree of deviation of the shape of the region from the circle can be used.
  • the average phase fluctuation ⁇ defined by the following equation (3) can be used as an index value indicating the randomness of the arrangement of the phase difference amounts in a plurality of pixels forming the phase difference image of the sphere.
  • ⁇ 0 is the minimum value of the phase difference amount in a predetermined range in a plurality of pixels forming the phase difference image
  • ⁇ N is the maximum value of the phase difference amount in the predetermined range.
  • L ( ⁇ ) is the perimeter of the isophase line at an arbitrary phase ⁇ within the above-mentioned predetermined range
  • a ( ⁇ ) is the area of a region surrounded by the isophase line of the perimeter L ( ⁇ ).
  • the average phase fluctuation ⁇ is minimum when the shape of the region surrounded by the isophase line is a perfect circle, and increases as the shape of the region surrounded by the isophase line increases as the shape departs from the circle. That is, the higher the randomness of the shape of the region surrounded by the equal phase lines, the larger the average phase fluctuation ⁇ .
  • the average phase fluctuation ⁇ in the phase difference image of the sphere corresponding to the undifferentiation rate of 99% shown in FIGS. 8A and 8B is 13.6, which corresponds to the undifferentiation rate of 87% shown in FIGS. 9A and 9B.
  • the average phase fluctuation ⁇ in the phase difference image of the sphere was 18.9.
  • the sphere in a lot with a relatively low undifferentiation rate contains a plurality of cells that have deviated from the undifferentiated state, thereby reducing the homogeneity inside the sphere. As a result, the randomness of the arrangement of the phase difference amounts in the plurality of pixels constituting the phase difference image of the sphere increases, and the average phase fluctuation ⁇ increases.
  • the average phase fluctuation ⁇ as an index value indicating the randomness of the arrangement of the phase difference amounts in a plurality of pixels constituting the phase difference image of the sphere, the progress of differentiation of the cells constituting the sphere can be determined. It is possible to estimate without destroying the cells.
  • FIG. 10A is a diagram illustrating a representative example of a phase contrast image of a sphere that is an aggregate of iPS cells extracted from a lot having a cell viability of 87.3% in the lot.
  • FIG. 10B is a contour diagram showing a distribution of the amount of phase difference in the phase difference image shown in FIG. 10A.
  • FIG. 11A is a diagram illustrating a representative example of a phase contrast image of a sphere that is an aggregate of iPS cells extracted from a culture lot in which the cell survival rate in the lot is 59.2%.
  • FIG. 11B is a contour diagram showing a distribution of a phase difference amount in the phase difference image shown in FIG. 11A.
  • a healthy cell maintains a constant internal refractive index different from the refractive index of a medium due to its homeostasis.
  • dead cells lose homeostasis and the internal refractive index becomes substantially the same as the refractive index of the medium. Therefore, spheres in a culture lot with a relatively high cell viability are considered to have higher internal homogeneity than spheres in a culture lot with a relatively low cell viability. Therefore, in the phase contrast image of the sphere in the culture lot in which the cell viability is relatively high, as shown in FIG.
  • the shape of the region surrounded by the equiphase lines connecting the pixels having the same phase difference amount Has a shape close to a circle, and the equiphase lines are distributed concentrically.
  • the arrangement of the phase difference amounts in a plurality of pixels constituting the phase difference image becomes random, The shape of the region surrounded by the equal phase lines is lost. That is, the survival rate of the cells constituting the sphere is reflected in the randomness of the arrangement of the phase difference amounts in the plurality of pixels constituting the phase difference image of the sphere. Therefore, the average phase fluctuation ⁇ can be used for determining the survival rate of the cells in the sphere.
  • the average phase fluctuation ⁇ in the phase difference image of the sphere corresponding to the cell viability of 87.3% shown in FIGS. 10A and 10B is 5.77, and the cell viability shown in FIGS. 11A and 11B.
  • the average phase fluctuation ⁇ in the phase difference image of the sphere corresponding to 59.2% was 11.08.
  • Spheres in lots with relatively low cell viability have reduced homogeneity inside the sphere due to the inclusion of many dead cells inside. As a result, the randomness of the arrangement of the phase difference amounts in the plurality of pixels constituting the phase difference image of the sphere increases, and the average phase fluctuation ⁇ increases.
  • the survival rate of the cells constituting the sphere can be determined by the cell Can be estimated without destroying.
  • the determination method includes, for a plurality of spheres included in a determination target lot, the above-described index value indicating the randomness of an array of phase difference amounts in a plurality of pixels included in a sphere phase difference image ( (Hereinafter referred to as a first index value) and deriving a second index value indicating a correlation between the sphere particle size and performing a determination on the determination target lot based on the second index value.
  • a first index value average phase fluctuation ⁇ can be used.
  • FIG. 12 is a graph showing the correlation between the sphere particle size and the average phase fluctuation ⁇ obtained for a plurality of spheres included in each of two lots whose undifferentiation rates are 87% and 99%, respectively. As shown in FIG. 12, it was found that the average phase fluctuation ⁇ tends to increase as the sphere particle size increases.
  • the sphere particle size dependence of the average phase fluctuation ⁇ can be considered to be characteristic of a cell line, a three-dimensional culture process, and a differentiation induction process.
  • spheres having a small particle size tend to have uniform progression of differentiation, whereas spheres having a large particle size tend to have uneven progression of differentiation, and
  • the fact that the size dependence of the cell density in the sphere differs depending on the culture and / or differentiation induction process is considered to be a factor that the average phase fluctuation ⁇ has the sphere particle size dependence.
  • the correlation between the sphere particle size and the average phase fluctuation ⁇ illustrated in FIG. 12 can be fitted by, for example, a function represented by the following equation (4). That is, the correlation between the sphere particle size and the average phase fluctuation ⁇ can be represented by an approximate expression using the function of Expression (4).
  • X is a sphere particle size
  • Y is an average phase fluctuation ⁇
  • A is a constant.
  • the constant A in the equation (4) can be used as an index value (a second index value) that indicates (correlates) the correlation between the sphere particle size and the average phase fluctuation ⁇ .
  • FIG. 13 is a graph showing the correlation between the constant A of Expression (4) and the undifferentiation rate in the two lots having different undifferentiation rates shown in FIG.
  • the undifferentiation rate of the cells in the determination target lot is estimated based on the constant A, for example. It is possible.
  • the undifferentiation rate of the determination target lot is determined based on the constant A (the second index value) which is an index value indicating the correlation between the average phase fluctuation ⁇ (the first index value) and the sphere particle size. It is possible to make an estimation, and it is possible to make, for example, a pass / fail judgment on the determination target lot based on the estimated undifferentiation rate.
  • FIG. 14 shows the results obtained for a plurality of spheres included in each of the four lots in which the viability of cells in the lot is 59.2%, 69.8%, 81.5%, and 87.3%, respectively.
  • 5 is a graph showing a correlation between a sphere particle size and an average phase fluctuation ⁇ .
  • the point that the average phase fluctuation ⁇ has a sphere particle size dependency is as described above.
  • FIG. 14 it was found that there was a difference in the correlation between the sphere particle size and the average phase fluctuation ⁇ between lots having different survival rates. That is, the difference in the cell survival rate between lots is reflected in the correlation between the sphere particle size and the average phase fluctuation ⁇ .
  • the correlation between the sphere particle size and the average phase fluctuation ⁇ shown in FIG. 14 can be fitted by, for example, the function shown in equation (4). That is, the correlation between the sphere particle size and the average phase fluctuation ⁇ can be represented by an approximate expression using the function of Expression (4).
  • the constant A which is an index value (second index value) characterizing the correlation between the sphere particle size and the average phase fluctuation ⁇ in the lot having the survival rate of 69.8%
  • FIG. 15 is a graph showing the correlation between the constant A of Expression (4) and the cell viability in the four lots having different cell viabilities shown in FIG.
  • the constant A the second index value
  • the constant A the second index value
  • the index value indicating the correlation between the average phase fluctuation ⁇ the first index value
  • the sphere particle size the cells in the lot for the determination target lot are determined. It is possible to estimate the survival rate of the determination target lot based on the estimated survival rate of the cells.
  • the randomness of the arrangement of the phase difference amount in a plurality of pixels constituting the phase difference image of the sphere May be derived.
  • the component that depends on the shape of the sphere is a surface that is gentle with respect to the pixel size and forms a basic shape of the sphere surface in the phase difference image of the sphere, and is a polynomial surface such as a quadratic function and a cubic function.
  • FIG. 16 shows a shape component-removed image (right diagram) in which randomness (spatial variation) of the phase difference amount is extracted by performing a process of removing a component depending on the shape of the sphere from the phase difference image of the sphere (left diagram).
  • the autocorrelation function derived for the shape component-removed image (the right diagram in FIG. 16) can be used as an index value indicating the randomness of the arrangement of the phase difference amounts in a plurality of pixels constituting the sphere phase difference image. is there. That is, the randomness (spatial variation) of the phase difference amount in the phase difference image of the sphere can be quantified by the autocorrelation function. Accordingly, it is possible to estimate the undifferentiation rate and the survival rate of the cells for the sphere or the lot to be determined including the sphere based on the autocorrelation function derived for the shape component-removed image (the right diagram in FIG. 16). .
  • the autocorrelation function obtained as described above is compared with, for example, a reference sample whose cell viability and undifferentiation rate are known, to determine whether the sphere or a lot to be determined including the sphere is good or bad. It is possible to make a decision.
  • the two-dimensional power spectrum derived for the shape component-removed image (the right diagram in FIG. 16) can be used as an index value indicating the randomness of the arrangement of the phase difference amounts in a plurality of pixels constituting the phase difference image of the sphere. It is.
  • the two-dimensional power spectrum P in the two-dimensional Fourier transform spectrum ⁇ (kx, ky) of the phase difference image ⁇ (x, y) is represented by the following equation (5).
  • kx and ky are spatial frequencies.
  • the randomness (spatial variation) of the phase difference amount in the phase difference image of the sphere can be quantified by the slope of the power spectrum illustrated in FIG. 17 and the function fitting. Then, based on the quantified numerical values, it is possible to estimate the undifferentiation rate and the survival rate of the cells for the sphere or the lot to be determined including the sphere.
  • the two-dimensional power spectrum obtained as described above for example, by comparing the survival rate and undifferentiation rate of the cell with a standard sample known, for the sphere or a lot to be determined containing the sphere, for example, Pass / fail judgment can be made.
  • the same can be applied to the autocorrelation function, which is the inverse Fourier transform of the power spectrum, according to the Wiener-Khintchine theorem.
  • Imaging system 10 Hologram optical system 11
  • Laser light source 12 Beam splitter 13
  • Collimating lens 14 samples 15
  • Objective lens 17 Imaging lens 18
  • CMOS camera 20 Optical fiber 21
  • Collimating lens 34 dichroic mirror 500 computers 502
  • Main storage device 503 Auxiliary storage device 504
  • Communication interface 505 display 506
  • Auto Focus Program 507 bus IP phase difference image ⁇ phase difference ⁇ B Background phase Phase Phase of the area where ⁇ S sphere exists ⁇ k Phase difference of one pixel k pixels w curve half width ⁇ Average phase fluctuation

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Abstract

L'invention concerne un procédé de détermination qui permet de déterminer de manière simple et non destructive l'état d'un agrégat de multiples cellules formées par culture tridimensionnelle. Dans ce procédé de détermination, une image de différence de phase d'un agrégat de multiples cellules est générée à partir d'un hologramme capturé de l'agrégat. Une première valeur d'indicateur dérivée indique un caractère aléatoire d'un ensemble des différences de phase dans les multiples pixels constituant l'image de différence de phase. L'état des cellules configurant un agrégat est déterminé sur la base de la première valeur d'indicateur.
PCT/JP2019/031862 2018-09-28 2019-08-13 Procédé de détermination WO2020066348A1 (fr)

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